Evidence map›Paper›PMID 31234531›Full record

ArticleNon-coding RNA2019

The Impact of Population Variation in the Analysis of microRNA Target Sites.

Mohab Helmy, Andrea Hatlen, Antonio Marco

Abstract read
In one paragraph

Article in Non-coding RNA, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. PopTargs: a database for studying population evolutionary genetics of human microRNA target sites.Database : the journal of biological databases and curation · 2019
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Mohab HelmySchool of Biological Sciences, University of Essex, Colchester CO4 3SQ, UK. mhaelb@essex.ac.uk.
Andrea HatlenSchool of Biological Sciences, University of Essex, Colchester CO4 3SQ, UK. a.hatlen@essex.ac.uk.
Antonio MarcoSchool of Biological Sciences, University of Essex, Colchester CO4 3SQ, UK. amarco.bio@gmail.com.ORCID 0000-0002-8603-7503

Funding

Wellcome Trust 200585/Z/16/Z
6 · The paper itself

Abstract

The impact of population variation in the analysis of regulatory interactions is an underdeveloped area. MicroRNA target recognition occurs via pairwise complementarity. Consequently, a number of computational prediction tools have been developed to identify potential target sites that can be further validated experimentally. However, as microRNA target predictions are done mostly considering a reference genome sequence, target sites showing variation among populations are neglected. Here, we studied the variation at microRNA target sites in human populations and quantified their impact in microRNA target prediction. We found that African populations carry a significant number of potential microRNA target sites that are not detectable in the current human reference genome sequence. Some of these targets are conserved in primates and only lost in Out-of-Africa populations. Indeed, we identified experimentally validated microRNA/transcript interactions that are not detected in standard microRNA target prediction programs, yet they have segregating target alleles abundant in non-European populations. In conclusion, we show that ignoring population diversity may leave out regulatory elements essential to understand disease and gene expression, particularly neglecting populations of African origin.

Indexed as

evolutiongene regulationhuman populationsmicroRNA target predictionmiRNAs

Identifiers

PMID31234531
PMCPMC6630466

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.